In current systems, the flexibility resulting from the existing large set of parameters included in the different algorithms cannot be fully used because of its complexity. In the planning stage, homogeneous networks are normally considered, as the large set of parameter makes the detailed planning process on a cell-by-cell basis a time-consuming task. As a consequence, the operators fix parameters to a common set of default values shared between cells, even if no optimum performance in terms of quality/capacity is reached. This homogeneity hypothesis may be far from reality, where interference or propagation severity can vary both in time and space over the network.
Moreover, a few operators extend the parameter optimisation by classifying the cells in accordance with certain scenarios like rural, urban, tunnel, indoors etc. and/or in accordance with the layer/band used (like Macro900/1800, Micro900/1800, Pico1800, Motorway900). So, the cells are divided into scenario groups or layer/band groups, and common default parameter values are shared which, however, are not optimum.
In those cases where new features are enabled, so-called field trials are required. During the tuning process, conclusions from parameter changes are difficult to derive, and final settings are nearly always on the safe side with its limited results. Moreover, such trials are normally focused on global parameters of features under study, and parameter optimisation of adjacent cells is hardly ever done. So, differences between adjacent cells are rarely considered due to a high effort required. Therefore, the potential of so-called adjacency parameters is not fully exploited.
A final limited parameter tuning based on cell/area level performance indicators is normally carried out only over those cells where performance problems are existing.
Even if an optimum value were reached by means of the above-mentioned trials, changes in traffic or environment conditions, like the installation of new cells, changes of interference level by frequency re-planning etc., would force a further re-tuning process of the parameter base, where no automatic reactive process is currently in use. Such a situation could be analysed as a result of slow trends, like the change of the number of user registrations, or fast changes, e.g. of the number of connections, during a short time period, like an hour or a day.
The obvious conclusion is the inability to grasp the full flexibility of the wide set of parameters.
In particular, parameters defining the cell operational area during the idle (camping) mode and the connection mode are not synchronised. In fact, cell attractiveness during connection mode may be completely different from idle mode due to traffic management strategies, causing unnecessary flow of users. The final result will be waste of bandwith in signalling and risk of dropped calls during the handover process.
From this analysis, it is obvious that unnecessary handover may be avoided if users camp on the cell which they are more likely to end-up in. Doing so, a great potential performance gain may be achieved. Moreover, operators may benefit from an automatic individual (i.e. cell based) optimising and tuning process. This would help operators in the tuning process and offer cost savings and improved performance, despite network inhomogeneities both in space (i.e. cell) and time (e.g. day or hour).